headshot of Fuheng wearing a white collared shirt with dogs and black rimmed glasses

This article was originally published by Andrew Masuda with the College of Engineering. 

UCSB PhD student receives esteemed fellowship to improve efficiency and privacy of data


View the complete news press here


(Santa Barbara, Calif.) – Fuheng Zhao, a third-year PhD student in UC Santa Barbara’s Computer Science (CS) Department, has received a prestigious Microsoft Research PhD Fellowship. The fellowship funds two years’ worth of tuition and fees, and provides an annual cash stipend of $42,000. Fellows also receive opportunities to build relationships and collaborations with Microsoft research teams. The technology company launched the global fellowship program to identify and empower the next generation of exceptionally talented computer science researchers. According to Microsoft Research, the program received a record number of applications this year, and the recipients should interpret the fellowships as recognition of their accomplishments and the potential for future impact Microsoft sees in them and their research.

“Receiving a Microsoft Research PhD Fellowship is a tremendous honor,” said Zhao. “Microsoft
Research has always been at the forefront of technological advancements. Connecting with its
research community will provide me with the exciting opportunity to gain insights into real-world
problems and create innovative solutions for positive change. The fellowship will also accelerate
the pace of my research and allow me to keep exploring exciting problems.”
Co-advised by distinguished professors of computer science Divyakant Agrawal and Amr El
, Zhao’s primary research interests lie in the fields of data systems, algorithms, and
privacy. His work involves performing data summarization — which refers to simplifying
generated data in an easily comprehensible and informative manner as efficiently and privately
as possible.

“Data summarizations should help systems and applications learn critical information and keep
an individual user’s information safe and confidential,” said Zhao, who received the CS
Department’s 2021-’22 Outstanding Publications Award. “I believe that efficient and private data
summaries are critical components in the next-generation of big data management systems and
data-intensive applications.”

Zhao started at UCSB as an undergraduate physics major, but he transferred into CS once he
discovered his passion for computing. After completing his bachelor’s degree in computer
science, he enrolled in UCSB’s CS PhD program because of his interest in databases, an area
in which Agrawal and El Abbadi are considered leaders in the global community. He also
immersed himself in the university’s spirit of innovation and collaboration, which has led to him
work on projects with computer science assistant professor Yu-Xiang Wang, an expert in
machine learning and privacy, as well as with computer science assistant professor Arpit
, an expert in networking systems.

Barely into his third year of the PhD program, Zhao has already had three publications
published at top conferences. Two papers were selected by one of the premiere database
events, the Very Large Data Bases (VLDB) Conference, while the third was accepted by the top
machine learning conference, the Neural Information Processing Systems (NeurIPS)

“Fuheng is amazing! He has incredible insights and is very hard working with diverse interests,”
said El Abbadi, a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), the
American Association for the Advancement of Science (AAAS), and the Association for
Computing Machinery (ACM). “He is strong theoretically, has a keen systems sense with a

special talent for identifying practical problems that have not been addressed adequately, and
has a knack for developing impressive and elegant solutions.”
In his PhD dissertation, Zhao is addressing an important problem of data summarization over
large amounts of data, extracting key properties of big data that are critical for large-scale data
analysis and building machine learning models.

“There is a large amount of prior research on this topic, but Fuheng’s work stands apart
because the algorithms he has developed can be readily used in the context of large-scale
databases that power internet-scale applications at Google, Facebook, and Amazon,” explained
Agrawal, a Fellow of IEEE, AAAS, and ACM, who added that Zhao’s selection was a testament
to the quality of UCSB’s Computer Science Department. “This fellowship not only signifies the
strength of the computer science graduate program at UCSB, but also establishes that our
undergraduate program is equally strong.”

Behind the support of his co-advisors, Zhao says that his research is aimed not at receiving
short-term rewards, but rather on solving real-world problems that he finds exciting and
intriguing. He is inspired by impactful works like the Bloom filter, a probabilistic data structure,
conceived in 1970, that is still used to rapidly and memory-efficiently determine if an item is
present in a dataset.

“I hope that my research will positively impact users’ productivity, minimizing system-resource
costs, and protecting our privacy and rights,” he said. “I will continue exploring data
summarization in-depth to advance the frontier and broaden my work’s scope to constructively
impact other areas, such as machine learning and fairness.”

Since its creation in 1999, the Microsoft Research PhD Fellowship program has supported more
than seven hundred fellows from around the world, many of whom have gone on to work at
Microsoft or elsewhere within the technology industry, or accepted faculty positions.